The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Heidi matrix: nearest neighbor driven high dimensional data visualization
Proceedings of the ACM SIGKDD Workshop on Visual Analytics and Knowledge Discovery: Integrating Automated Analysis with Interactive Exploration
Using R-trees for interactive visualization of large multidimensional datasets
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part II
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High dimensional index structures are used to efficiently answer range queries in large databases. Visualization of such index structures helps in: (a) visualization of the data set in a hierarchical format of the index structure, (b) "explorative querying" on the data set, similar to explorative browsing on the web, (c) index structure diagnostics: visualizing the structure along with its performance statistics enables the user to make changes to structure for better performance. To the best of our knowledge, there is no such visualization for high dimensional index structures.